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AI agent for conversion rate optimization specialists

Analytics Funnel Hypothesis Agent

Find the cause of the biggest funnel drop through a series of tested hypotheses.

Analytics Funnel Hypothesis Agent: what goes in, what the agent does and what you get

What it does

Your analytics show that 60% of people leave at step two of sign-up, but nobody knows why. This agent reads the funnel data and finds the biggest drop between steps. It opens the matching screens and inspects them for likely causes, such as a long form, an unclear label, a slow load or a hidden button. It writes a ranked list of hypotheses and proposes a small test for the top one, with the metric and the sample needed. When the test has run, it reads the result. If the hypothesis fails, it drops it and moves to the next one. If it works, it records the lift and checks whether the drop moved to a later step. The designer approves each test before it goes live. Edge case: the drop only appears on mobile, so the agent splits the data by device first.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
ApprovedYes, continueYes, continueNoNo 1 STARTS WHEN Weekly funnel data arrives 2 USES A TOOL Read funnel data and split it by device and source 3 DOES Find the step with the largest drop 4 USES A TOOL Inspect the matching screens and load times 5 DOES Write ranked hypotheses with a proposed test 6 YOU APPROVE Designer approves the test before it goes live 7 USES A TOOL Read the test results when the sample is reached 8 CHECKS THE RESULT Did the test beat the control? If not: drop this hypothesis and propose the next one onthe list. Back to step 5. 9 CHECKS THE RESULT Did the drop simply move to a later step? If not: rerun the analysis on the new weakest step. Backto step 2. 10 RESULT Recorded finding and next test
Read the steps as a list
  1. Weekly funnel data arrives
  2. Read funnel data and split it by device and source
  3. Find the step with the largest drop
  4. Inspect the matching screens and load times
  5. Write ranked hypotheses with a proposed test
  6. Designer approves the test before it goes liveThe agent waits here for your OK.
  7. Read the test results when the sample is reached
  8. Did the test beat the control?If not: drop this hypothesis and propose the next one on the list. Back to step 5.
  9. Did the drop simply move to a later step?If not: rerun the analysis on the new weakest step. Back to step 2.
  10. Recorded finding and next test

How it decides

It ranks hypotheses by the size of the drop, the evidence on the screen and how cheap the test is. A hypothesis fails when the test shows no lift beyond the noise range.

  • Look at a step only if it has at least 500 visitors in the period
  • Rank hypotheses with the cheapest test first when evidence is equal
  • Call a test a win only at a lift above 5% with the sample reached
  • Always compare mobile and desktop before forming a hypothesis

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Minimum visitors per step (default 500)
  • Lift needed to call a win (default 5%)
  • Funnels to watch
  • Test tool and sample size rule
  • Review day of the week

What keeps you in control

It always asks you first

  • Designer approves each test before it is started

Hard limits

  • Never launch a test or change a live page
  • Never report a win before the sample size is reached

It stops when

  • Done: a winning change is recorded and the funnel is rechecked
  • Stop: three hypotheses in a row fail, so ask the designer for user research

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensSign-up loses 58% at step two, mostly on phones. The agent finds a seven-field form that needs scrolling and proposes cutting it to three fields. The test runs for 10 days with 1,800 visitors, and completion rises from 42% to 44%, which is inside the noise range. The agent drops the hypothesis and proposes a visible progress bar next, which the designer approves.

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